.. highlight:: kotlin .. raw:: html Interacting with a node ======================= .. contents:: Overview -------- You should interact with your node using the `CordaRPCClient`_ library. This library that allows you to easily write clients in a JVM-compatible language to interact with a running node. The library connects to the node using a message queue protocol and then provides a simple RPC interface to interact with the node. You make calls on a JVM object as normal, and the marshalling back and forth is handled for you. .. warning:: The built-in Corda webserver is deprecated and unsuitable for production use. If you want to interact with your node via HTTP, you will need to stand up your own webserver, then create an RPC connection between your node and this webserver using the `CordaRPCClient`_ library. You can find an example of how to do this using the popular Spring Boot server `here `_. Connecting to a node via RPC ---------------------------- `CordaRPCClient`_ provides a ``start`` method that takes the node's RPC address and returns a `CordaRPCConnection`_. `CordaRPCConnection`_ provides a ``proxy`` method that takes an RPC username and password and returns a `CordaRPCOps`_ object that you can use to interact with the node. Here is an example of using `CordaRPCClient`_ to connect to a node and log the current time on its internal clock: .. container:: codeset .. literalinclude:: example-code/src/main/kotlin/net/corda/docs/ClientRpcExample.kt :language: kotlin :start-after: START 1 :end-before: END 1 .. literalinclude:: example-code/src/main/java/net/corda/docs/ClientRpcExampleJava.java :language: java :start-after: START 1 :end-before: END 1 .. warning:: The returned `CordaRPCConnection`_ is somewhat expensive to create and consumes a small amount of server side resources. When you're done with it, call ``close`` on it. Alternatively you may use the ``use`` method on `CordaRPCClient`_ which cleans up automatically after the passed in lambda finishes. Don't create a new proxy for every call you make - reuse an existing one. For further information on using the RPC API, see :doc:`tutorial-clientrpc-api`. RPC permissions --------------- For a node's owner to interact with their node via RPC, they must define one or more RPC users. Each user is authenticated with a username and password, and is assigned a set of permissions that control which RPC operations they can perform. Permissions are not required to interact with the node via the shell, unless the shell is being accessed via SSH. RPC users are created by adding them to the ``rpcUsers`` list in the node's ``node.conf`` file: .. container:: codeset .. sourcecode:: groovy rpcUsers=[ { username=exampleUser password=examplePass permissions=[] } ... ] By default, RPC users are not permissioned to perform any RPC operations. Granting flow permissions ~~~~~~~~~~~~~~~~~~~~~~~~~ You provide an RPC user with the permission to start a specific flow using the syntax ``StartFlow.``: .. container:: codeset .. sourcecode:: groovy rpcUsers=[ { username=exampleUser password=examplePass permissions=[ "StartFlow.net.corda.flows.ExampleFlow1", "StartFlow.net.corda.flows.ExampleFlow2" ] } ... ] You can also provide an RPC user with the permission to start any flow using the syntax ``InvokeRpc.startFlow``: .. container:: codeset .. sourcecode:: groovy rpcUsers=[ { username=exampleUser password=examplePass permissions=[ "InvokeRpc.startFlow" ] } ... ] Granting other RPC permissions ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ You provide an RPC user with the permission to perform a specific RPC operation using the syntax ``InvokeRpc.``: .. container:: codeset .. sourcecode:: groovy rpcUsers=[ { username=exampleUser password=examplePass permissions=[ "InvokeRpc.nodeInfo", "InvokeRpc.networkMapSnapshot" ] } ... ] Granting all permissions ~~~~~~~~~~~~~~~~~~~~~~~~ You can provide an RPC user with the permission to perform any RPC operation (including starting any flow) using the ``ALL`` permission: .. container:: codeset .. sourcecode:: groovy rpcUsers=[ { username=exampleUser password=examplePass permissions=[ "ALL" ] } ... ] .. _rpc_security_mgmt_ref: RPC security management ----------------------- Setting ``rpcUsers`` provides a simple way of granting RPC permissions to a fixed set of users, but has some obvious shortcomings. To support use cases aiming for higher security and flexibility, Corda offers additional security features such as: * Fetching users credentials and permissions from an external data source (e.g.: a remote RDBMS), with optional in-memory caching. In particular, this allows credentials and permissions to be updated externally without requiring nodes to be restarted. * Password stored in hash-encrypted form. This is regarded as must-have when security is a concern. Corda currently supports a flexible password hash format conforming to the Modular Crypt Format provided by the `Apache Shiro framework `_ These features are controlled by a set of options nested in the ``security`` field of ``node.conf``. The following example shows how to configure retrieval of users credentials and permissions from a remote database with passwords in hash-encrypted format and enable in-memory caching of users data: .. container:: codeset .. sourcecode:: groovy security = { authService = { dataSource = { type = "DB", passwordEncryption = "SHIRO_1_CRYPT", connection = { jdbcUrl = "" username = "" password = "" driverClassName = "" } } options = { cache = { expireAfterSecs = 120 maxEntries = 10000 } } } } It is also possible to have a static list of users embedded in the ``security`` structure by specifying a ``dataSource`` of ``INMEMORY`` type: .. container:: codeset .. sourcecode:: groovy security = { authService = { dataSource = { type = "INMEMORY", users = [ { username = "", password = "", permissions = ["", "", ...] }, ... ] } } } .. warning:: A valid configuration cannot specify both the ``rpcUsers`` and ``security`` fields. Doing so will trigger an exception at node startup. Authentication/authorisation data ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The ``dataSource`` structure defines the data provider supplying credentials and permissions for users. There exist two supported types of such data source, identified by the ``dataSource.type`` field: :INMEMORY: A static list of user credentials and permissions specified by the ``users`` field. :DB: An external RDBMS accessed via the JDBC connection described by ``connection``. Note that, unlike the ``INMEMORY`` case, in a user database permissions are assigned to *roles* rather than individual users. The current implementation expects the database to store data according to the following schema: - Table ``users`` containing columns ``username`` and ``password``. The ``username`` column *must have unique values*. - Table ``user_roles`` containing columns ``username`` and ``role_name`` associating a user to a set of *roles*. - Table ``roles_permissions`` containing columns ``role_name`` and ``permission`` associating a role to a set of permission strings. .. note:: There is no prescription on the SQL type of each column (although our tests were conducted on ``username`` and ``role_name`` declared of SQL type ``VARCHAR`` and ``password`` of ``TEXT`` type). It is also possible to have extra columns in each table alongside the expected ones. Password encryption ~~~~~~~~~~~~~~~~~~~ Storing passwords in plain text is discouraged in applications where security is critical. Passwords are assumed to be in plain format by default, unless a different format is specified by the ``passwordEncryption`` field, like: .. container:: codeset .. sourcecode:: groovy passwordEncryption = SHIRO_1_CRYPT ``SHIRO_1_CRYPT`` identifies the `Apache Shiro fully reversible Modular Crypt Format `_, it is currently the only non-plain password hash-encryption format supported. Hash-encrypted passwords in this format can be produced by using the `Apache Shiro Hasher command line tool `_. Caching user accounts data ~~~~~~~~~~~~~~~~~~~~~~~~~~ A cache layer on top of the external data source of users credentials and permissions can significantly improve performances in some cases, with the disadvantage of causing a (controllable) delay in picking up updates to the underlying data. Caching is disabled by default, it can be enabled by defining the ``options.cache`` field in ``security.authService``, for example: .. container:: codeset .. sourcecode:: groovy options = { cache = { expireAfterSecs = 120 maxEntries = 10000 } } This will enable a non-persistent cache contained in the node's memory with maximum number of entries set to ``maxEntries`` where entries are expired and refreshed after ``expireAfterSecs`` seconds. Observables ----------- The RPC system handles observables in a special way. When a method returns an observable, whether directly or as a sub-object of the response object graph, an observable is created on the client to match the one on the server. Objects emitted by the server-side observable are pushed onto a queue which is then drained by the client. The returned observable may even emit object graphs with even more observables in them, and it all works as you would expect. This feature comes with a cost: the server must queue up objects emitted by the server-side observable until you download them. Note that the server side observation buffer is bounded, once it fills up the client is considered slow and will be disconnected. You are expected to subscribe to all the observables returned, otherwise client-side memory starts filling up as observations come in. If you don't want an observable then subscribe then unsubscribe immediately to clear the client-side buffers and to stop the server from streaming. For Kotlin users there is a convenience extension method called ``notUsed()`` which can be called on an observable to automate this step. If your app quits then server side resources will be freed automatically. .. warning:: If you leak an observable on the client side and it gets garbage collected, you will get a warning printed to the logs and the observable will be unsubscribed for you. But don't rely on this, as garbage collection is non-deterministic. If you set ``-Dnet.corda.client.rpc.trackRpcCallSites=true`` on the JVM command line then this warning comes with a stack trace showing where the RPC that returned the forgotten observable was called from. This feature is off by default because tracking RPC call sites is moderately slow. .. note:: Observables can only be used as return arguments of an RPC call. It is not currently possible to pass Observables as parameters to the RPC methods. In other words the streaming is always server to client and not the other way around. Futures ------- A method can also return a ``CordaFuture`` in its object graph and it will be treated in a similar manner to observables. Calling the ``cancel`` method on the future will unsubscribe it from any future value and release any resources. Versioning ---------- The client RPC protocol is versioned using the node's platform version number (see :doc:`versioning`). When a proxy is created the server is queried for its version, and you can specify your minimum requirement. Methods added in later versions are tagged with the ``@RPCSinceVersion`` annotation. If you try to use a method that the server isn't advertising support of, an ``UnsupportedOperationException`` is thrown. If you want to know the version of the server, just use the ``protocolVersion`` property (i.e. ``getProtocolVersion`` in Java). The RPC client library defaults to requiring the platform version it was built with. That means if you use the client library released as part of Corda N, then the node it connects to must be of version N or above. This is checked when the client first connects. If you want to override this behaviour, you can alter the ``minimumServerProtocolVersion`` field in the ``CordaRPCClientConfiguration`` object passed to the client. Alternatively, just link your app against an older version of the library. Thread safety ------------- A proxy is thread safe, blocking, and allows multiple RPCs to be in flight at once. Any observables that are returned and you subscribe to will have objects emitted in order on a background thread pool. Each Observable stream is tied to a single thread, however note that two separate Observables may invoke their respective callbacks on different threads. Error handling -------------- If something goes wrong with the RPC infrastructure itself, an ``RPCException`` is thrown. If you call a method that requires a higher version of the protocol than the server supports, ``UnsupportedOperationException`` is thrown. Otherwise, if the server implementation throws an exception, that exception is serialised and rethrown on the client side as if it was thrown from inside the called RPC method. These exceptions can be caught as normal. Connection management --------------------- It is possible to not be able to connect to the server on the first attempt. In that case, the ``CordaRPCClient.start()`` method will throw an exception. The following code snippet is an example of how to write a simple retry mechanism for such situations: .. sourcecode:: Kotlin fun establishConnectionWithRetry(nodeHostAndPort: NetworkHostAndPort, username: String, password: String): CordaRPCConnection { val retryInterval = 5.seconds do { val connection = try { logger.info("Connecting to: $nodeHostAndPort") val client = CordaRPCClient( nodeHostAndPort, object : CordaRPCClientConfiguration { override val connectionMaxRetryInterval = retryInterval } ) val _connection = client.start(username, password) // Check connection is truly operational before returning it. val nodeInfo = _connection.proxy.nodeInfo() require(nodeInfo.legalIdentitiesAndCerts.isNotEmpty()) _connection } catch(secEx: ActiveMQSecurityException) { // Happens when incorrect credentials provided - no point to retry connecting. throw secEx } catch(ex: RPCException) { // Deliberately not logging full stack trace as it will be full of internal stacktraces. logger.info("Exception upon establishing connection: " + ex.message) null } if(connection != null) { logger.info("Connection successfully established with: $nodeHostAndPort") return connection } // Could not connect this time round - pause before giving another try. Thread.sleep(retryInterval.toMillis()) } while (connection == null) } After a successful connection, it is possible for the server to become unavailable. In this case, all RPC calls will throw an exception and created observables will no longer receive observations. Below is an example of how to reconnect and back-fill any data that might have been missed while the connection was down. This is done by using the ``onError`` handler on the ``Observable`` returned by ``CordaRPCOps``. .. sourcecode:: Kotlin fun performRpcReconnect(nodeHostAndPort: NetworkHostAndPort, username: String, password: String) { val connection = establishConnectionWithRetry(nodeHostAndPort, username, password) val proxy = connection.proxy val (stateMachineInfos, stateMachineUpdatesRaw) = proxy.stateMachinesFeed() val retryableStateMachineUpdatesSubscription: AtomicReference = AtomicReference(null) val subscription: Subscription = stateMachineUpdatesRaw .startWith(stateMachineInfos.map { StateMachineUpdate.Added(it) }) .subscribe({ clientCode(it) /* Client code here */ }, { // Terminate subscription such that nothing gets past this point to downstream Observables. retryableStateMachineUpdatesSubscription.get()?.unsubscribe() // It is good idea to close connection to properly mark the end of it. During re-connect we will create a new // client and a new connection, so no going back to this one. Also the server might be down, so we are // force closing the connection to avoid propagation of notification to the server side. connection.forceClose() // Perform re-connect. performRpcReconnect(nodeHostAndPort, username, password) }) retryableStateMachineUpdatesSubscription.set(subscription) } In this code snippet it is possible to see that function ``performRpcReconnect`` creates an RPC connection and implements the error handler upon subscription to an ``Observable``. The call to this ``onError`` handler will be made when failover happens then the code will terminate existing subscription, closes RPC connection and recursively calls ``performRpcReconnect`` which will re-subscribe once RPC connection comes back online. Client code if fed with instances of ``StateMachineInfo`` using call ``clientCode(it)``. Upon re-connecting, this code receives all the items. Some of these items might have already been delivered to client code prior to failover occurred. It is down to client code in this case handle those duplicate items as appropriate. Wire security ------------- ``CordaRPCClient`` has an optional constructor parameter of type ``ClientRpcSslOptions``, defaulted to ``null``, which allows communication with the node using SSL. Default ``null`` value means no SSL used in the context of RPC. To use this feature, the ``CordaRPCClient`` object provides a static factory method ``createWithSsl``. In order for this to work, the client needs to provide a truststore containing a certificate received from the node admin. (The Node does not expect the RPC client to present a certificate, as the client already authenticates using the mechanism described above.) For the communication to be secure, we recommend using the standard SSL best practices for key management. Whitelisting classes with the Corda node ---------------------------------------- CorDapps must whitelist any classes used over RPC with Corda's serialization framework, unless they are whitelisted by default in ``DefaultWhitelist``. The whitelisting is done either via the plugin architecture or by using the ``@CordaSerializable`` annotation. See :doc:`serialization`. An example is shown in :doc:`tutorial-clientrpc-api`. .. _CordaRPCClient: api/javadoc/net/corda/client/rpc/CordaRPCClient.html .. _CordaRPCOps: api/javadoc/net/corda/core/messaging/CordaRPCOps.html .. _CordaRPCConnection: api/javadoc/net/corda/client/rpc/CordaRPCConnection.html